Daytime land surface temperature product - 60m - 31TGJ

Abstract

Developed through the SENWISE initiative, this Land Surface Temperature Monitoring (LSTM) representative dataset aims to support the preparation of the upcoming mission by emulating its expected data products. The dataset provides a consolidated, multi-temporal representation of daytime land surface temperature (LST), structured to be a proxy of the future LSTM data outputs. Data are provided at 60m resolution and are produced using Sentinel-3 LST product at 1km resolution through Kernel Driven Downscaling (KDD). Data collection covers the area of Sentinel 2 Tile: 32TGJ (WGS84, EPSG4326: 5.4627354, 43.2012113, 6.8757389, 44.2259751). LST is provided in Kelvin and stored with an offset of 150, a scale factor of 0.01.

FAIR Overall Score

Keywords

LSTM-LIKE, LST, HIGH RESOLUTION, KDD, SENWISE, SENTINEL

Legal constraints

CC-BY-4.0

FAIR Overall Score: %

Evaluated by F-UJI - An Automated FAIR Data Assessment Tool: https://doi.org/10.5281/zenodo.6361400

Findable 0%

Accessible 0%

Interoperable 0%

Reusable 0%

Findable Low

Accessible Low

Interoperable Low

Reusable Low

Snippet code

##### ----Explore and download STAC data with Python ----- #####

from pystac_client import Client

## Read the example catalog
URL = 'https://stac.eurac.edu/'
catalog = Client.open(URL)

## List the Collections in the given Catalog
stac_collections = list(catalog.get_collections())
print(f"Number of collections: {len(stac_collections)}")

## Print collection IDs
print("Collections IDs:")
for collection in stac_collections:
    print(f"- {collection.id}")
print("-------------------------")

## Retrieve a specific collection
collection = catalog.get_collection("Daytime_land_surface_temperature_product-60m–31TGJ")

## Search for items in the collection
collection_items = list(catalog.search(collections=['Daytime_land_surface_temperature_product-60m–31TGJ'], max_items=10).items())
print(collection_items)

## Retrieve a list of the first 10 items belonging to a specific collection
item = collection.get_item("NameOfTheItem")
#print(list(item.assets.items())[0:10])

##Print the band name and the href of a specific item retrieved from the previous list
print(item.assets["Daytime_land_surface_temperature_product-60m–31TGJ"].title)
print(item.assets["Daytime_land_surface_temperature_product-60m–31TGJ"].href)

## Print Item’s assets through the assets attribute, which is a dictionary
for asset_key in item.assets:
    asset = item.assets[asset_key]
    print("{}: {} ({})".format(asset_key, asset.href, asset.media_type))

## ------------- DONWLOAD COG files from a specific collection ------- ####
from pystac_client import Client
import requests

## Read the example catalog
URL = 'https://stac.eurac.edu/'
catalog = Client.open(URL)

## List the Collections in the given Catalog
stac_collections = list(catalog.get_collections())
# print(f"Number of collections: {len(stac_collections)}")

## Print collection IDs
print("Collections IDs:")
for collection in stac_collections:
	print(f"- {collection.id}")
print("-------------------------")

## Retrieve a specific collection
collection = catalog.get_collection("Daytime_land_surface_temperature_product-60m–31TGJ")

## Search for items in the collection
collection_items = list(catalog.search(collections=['Daytime_land_surface_temperature_product-60m–31TGJ'], max_items=10).items())
print(collection_items)

url_basepath = "https://eurac-eo.s3-eu-west-1.amazonaws.com/"
collection_url = url_basepath + "Daytime_land_surface_temperature_product-60m–31TGJ" + "/"
print(collection_url)
for item_id in collection_items:
	# item = item.assets[asset_key]
	print(item_id.id)
	cog_file = str(item_id.id + '.tif')
	url = collection_url + cog_file
	response = requests.get(url)
	with open(cog_file, "wb") as f:
		f.write(response.content)